RRE Blog

Airware: Democratizing Unmanned Aerial Vehicles

I first met the Airware (Unmanned Innovations at the time) team at the Lemnos Labs demo day in December, 2012. Working out of the Lemnos garage in the untrendy part of San Francisco, Jonathan Downey and the rest of the Airware team had a grand vision for Unmanned Aerial Vehicles (UAVs), which are often conflated with drones (all drones are UAVs, but not vice versa - drones are by definition autonomous).

Jonathan patiently explained to me that the autopilot, which comprises a significant portion of UAV deployment and maintenence costs, was stuck in a very old paradigm of blackboxed, special purpose units - much like buying a computer in the 80s. This might make sense for a $17M military UAV, but Jonathan also noted that we are at the dawn of cheap, small, general purpose UAVs - UAVs that might be bought or rented for agricultural, real estate, law enfocement, and more. Buying a special purpose black box autopilot for every new UAV use case didn't make sense.

Enter Airware. If traditional autopilots were IBM mainframes, Airware systems are personal computers: robust, general purpose systems, and the foundation upon which billions of dollars of productivity are generated by the end users.

Now, it's easy to have a grand vision - but Jonathan and his team lived and breathed aircraft, both manned and unmanned. Kent Goldman of First Round Capital has a very good post on why the passion of founders is important. Combined with the team's impressive academic and professional background in engineering and aeronautics, Airware was a no brainer for RRE.

Few things we look at have the potential to radically change the pace of technological development. We're proud to officially announce our seed investment in Airware, a company that we believe has the potential to do just that.

This is what consumer fatigue looks like

When the iPhone 5 and the iPad Mini came out, people joked that you would be able to own a comprehensive gradient of screen sizes between phone and tablet. Well, if you consider both Android and iOS, that turns out to be the case now:

: Click for full res. PSD file with layers provided here.

If you've walked into a Best Buy (people still do that, right?) recently or tried to browse online for a new phone or tablet, you've probably been overwhelmed by the choices. This overwhelming indecisiveness (#firstworldproblems) is known as "consumer fatigue," and Rahul Raghavan gives a pretty good summary on Quora:

Providing choice is very good up to a point. Even minor variations in product that provide a very superficial "choice" to consumers is beneficial (buyers find it empowering, sales go up).

Beyond this, paradoxically, too much choice overwhelms people to the extent that they end up paralyzed and don't choose anything. There are cases where reducing the number of variants of a product leads to increased sales (a famous experiment involving jams).

If you have to provide a lot of choice, divide the variants into a small number of clearly delineated categories, with a small number of choices in each category. Consumers then quickly choose their category of interest, then choose the product their want - Two less taxing choices are better than one large choice.

Some research suggests that the number of options where "good choice" becomes "bad choice" is about 7 - the same as Miller's Magic Number 7, the number of things that may be held in working memory by the average human.

A few years ago, one could have attributed consumer fatigue in the smartphone market to the novelty of the smartphone industry and companies taking a see-what-sticks approach to product design, which is common in young markets. My colleague Tom Loverro wrote a similar post two years ago about the state of the phone industry then.

But what explains the fatigue now? After the surge and death of many designs that accompany a growing industry, companies left standing quickly trim to what works and thereby reduce consumer fatigue. HTC rose from lowly OEM to brand-name prominence by churning out dozens of Android phones during the smartphone boom of 2011, and quickly came crashing back down in 2012. HTC then declared that it would focus on “less product, more exposure on those" - the result of which is the aptly-named HTC One. Samsung's website now only features its successful Galaxy line of Android phones. Apple is the only outlier, having been extraordinarily conservative with SKUs - iPhone and only iPhone - and made itself king of the smartphone market before branching out into tablets and other form factors. It has actually increased its consumer offerings during the swell and die-off in the smartphone market.

We go back to Rahul's point: if you have to provide a lot of choice, divide the variants into a small number of clearly delineated categories. It turns out that within brands, manufacturers have actually done a decent job of reducing fatigue and providing sets of choices:

: Samsung's Offerings

: Apple's Offerings

Samsung's offerings provide the same set of choices as Apple's: phone versus tablet, small versus big. The relatively rare Galaxy Mega I will discount as a dying breath of Samsung's make-all-the-phones philosophy.

Now, consumer fatigue arises when we conflate the reasonable choices that independent manufacturers offer. As a result of a mind-numbingly inefficient IP law system, every manufacturer is arriving at the same set of choices just slightly differently than every other manufacturer to avoid getting sued - and the result is our wonderfully messy gradient of choices.

: Source: http://blog.thomsonreuters.com/index.php/mobile-patent-suits-graphic-of-the-day/

In a clear example of competition and patent law hurting the consumer, smartphone manufacturers are doing a lot of redundant work (Apple maps) and forcing each other to find kludgey workarounds (no Google ActiveSync in iOS using Microsoft Exchange?). Although the industry is moving beyond the point where there are more SKUs per manufacturer than you can count on two hands, there's still a lot of progress to be made in patent law and protocol standardization before we reach the sort of techno utopia that all TED Talks seem to be all about these days.

Is your startup a feature, a product or a business?

Through my development as a junior VC, I regularly find myself asking questions similar to those of my entrepreneur friends.

Without many ghosts of pitches past, I glean knowledge from others’ refined judgement and execution. Take it this way: venture capitalists are paid to act on a point of view, ideally one that proves profitable. But how do VCs identify what will return multiples on their money, many times years ahead of an outcome? What do they pay attention to when making such decisions?

Even the most basic of feedback can seem confusing.

Just one thing

Frequently, founders are told “Do one thing and do it well.” Instagram is an oft-cited winner that honed in on a simple task: mobile photo sharing. Instagram’s former self, Burbn, was scrapped after feeling cluttered and overrun with features, with its wider offerings around location check-ins and social event planning. Instagram CEO Kevin Systrom said, “Focusing on one thing and doing it really, really well can get you very far.” In fact, $1 billion far.

Cue envy. Cue funding funneling to players riding at the coattails. There were so many Instagrams for video at one point that The Next Web felt compelled to pick just the top ten.

Okay, that’s easy enough. Crush it performing one task.

Not so fast. Founders also sometimes hear that they are not building real businesses. Instead, they are declined as FNACs - just buttons on a page. Well, any number of technology behemoths could build that; how defensible could this be? Thanasis Delistathis from New Atlantic Ventures cleverly pointed out that blue chip companies like Apple, Google, and Microsoft “have built such a cash cow in a business line…that in their search for growth spend lots of money to give features away.”

But as we’ve seen, the ecosystem can bear fruit to many winners. Spark Capital’s Andrew Parker astutely cut up the Craigslist homepage to show how the directory has given way to category-oriented companies like HomeAway, OkCupid, and StubHub. It’s an image regularly shared across the web, though infrequently commenters address Parker’s amazement of how Craigslist continues to compete, “if not dominate”, with basic HTML/CSS UI and fewer features.

So, how does one define and identify this “one thing”? What exactly is a feature? A product? And, what do investors consider to be businesses?

A matter of perspective

Here’s the secret: investors themselves often struggle to delineate the difference among these identities. Wasn’t Twitter just the status bar feature on Facebook? Facebook Places launched in 2010, a year after Foursquare. Did Foursquare then qualify as a feature?

Bill Gurley from Benchmark Capital drew criticism after claiming Dropbox to be a “major disruption” because the team “had taken a hard problem – file synchronization — and made it brain dead simple” as disbelievers fell into the Steve Jobs camp that file sync is a feature, not a product. Rory O’Driscoll from Scale Venture Partners came to Gurley’s defense, stating that the feature label should be taken as a compliment. “To get any traction in software today you have to start with a feature — an atomic unit of delight. You have to solve one problem superbly.” Dropbox is currently valued at over $4 billion.

Google, Yahoo, and more recently Mailbox are other examples that were turned away, or funded, based on subjective viewpoints of their status. Where did startups like Disqus and UserVoice first fit in? Attempting to find the common thread was perplexing.

Pulling discussions together, features perform an action. Products, normally a package of features, solve a problem. Businesses, potentially a package of products, provide recurring value to users. Ideally, these users offer up some measurable currency (data, time, cash) in exchange, otherwise it is not a particularly sustainable business. Do keep in mind that what may be disruptive and novel today may only be a button on a page tomorrow, shifting investors’ attitudes accordingly. Further, it could be argued that at the early stage investors almost never see full-blown companies, but kernels of opportunity through features and products.

Cool. How does this apply to raising venture capital?

Evaluating opportunity

Jason Mendelson from Foundry stated that the discussion around FNACs ultimately comes down to single question: is this a big enough opportunity in which to invest?

Venture capitalists evaluate the size of an opportunity centered on one primary ‘thing’: anticipation. Investors anticipate the behavior of competitors (current and prospective) and customers (also current and prospective), before checking into any concerns regarding management, the government, and black swans. Their interest is to pinpoint, then pile their time and capital into, high potential exits. They place bets on predictions, encouraged by evidence.

When considering competitors, VCs will ask, “What is challenging to replicate?” With incumbents and future contenders boasting perhaps more talent, funding, and scale, where is the edge? For some, this may be their sticky network (Evernote, Buzzfeed, WhatsApp), for others, a growing pool of insightful information gathered from complex algorithms (Palantir, bitly, Etsy). Is this particular opportunity unassailable?

When considering customers, venture capitalists will ask, “What are the trends?” Where are the signals indicating that people are climbing over themselves to be a customer and evangelizing the solution to peers because it is simply so special? Is the dynamic likely to continue and grow into the future? A good example might be Airbnb, which has grown by leaps and bounds domestically and abroad despite the challenge of building a two-sided marketplace and initial skepticism of renting a stranger’s home.

The shift of the experience from experimental (at the least this will make for a good story) to utilitarian (I just want the most affordable/delightful/convenient stay) is key for unlocking hearts and wallets of the masses.

Getting back to this “one thing” – ignore the labels. Utilize focus to be one step ahead. Build a powerhouse, not a business.

8 Things Your VC Won't Tell You

Venture capitalists, especially those investing at the early stage, could be described as "relationship capitalists". You'll often hear how investors approach their commitments like a marriage, and that they think long and hard about with whom they want to go to bed. Avoid picturing that second part.

But the VC mystique can be inexplicable at times. Why do they send such curt emails? What the #%$! do they mean by "traction"? Are they even paying attention?!

Here are some things they might be thinking (but probably won't flat-out say) during the courtship process, and how you can prepare, take ownership, and rock the pitch.

1. "I can't remember what you do."

VCs have countless meetings with entrepreneurs, and review even more pitches remotely. Chances are, you've scheduled a meeting weeks ahead of time due to a jammed calendar and travel itineraries. Or, you got turned down before, months or years ago, and are having a follow-up discussion.

Don't take it personally if you're met with a semi-blank stare. Start the meeting with a brief sentence or two that subtly describes your business and background. It'll help prevent confusion (and potentially glazed eyes) deeper into the conversation.

2. "I don't get your product."

Speak simply, and get to the point. VCs understand that you're 1,000% excited to be tackling the problems you're tackling, but stick with one storyline at a time. Reading between the lines is a little too much work. Treat them as if they were a valuable customer. At the very least, it's great practice for when that is the case.

Moreover, ensure that the investor does, in fact, understand your business, rather than just thinking so. One approach might be to say, "Now that I've told you what we do, I'd be very interested in how you describe the business from your perspective." You'll likely gain some enlightening feedback on your pitch.

Of course, the above implies that you know your business and market inside and out. The less you understand, the less value you're likely to provide to your startup, and the less an investor will want to get involved.

3. "I know I've heard of others doing this..."

Have a clear handle on your competitive set and address them outright. Entrepreneurs should be fluent in the goings-on of their industry, and have a firm understanding of how their business differentiates itself. Unless the VC is very familiar with your space, they may withdraw temporarily as they rack for comps.

This is also a common test. Either way, be prepared to knock it out of the park.

4. "Can I add value to this business?"

Illustrate how your VC can provide value to your enterprise. Every VC wants to feel like s/he can offer more help than signing a check; your investors want and should be a part of your braintrust. Demonstrate that you know the firm and profile, and can explain how this will take your company to the next level (which, with any luck, will reap benefits for them too).

5. "You're not solving a real problem."

Answer this: How is your business changing the world? Put in other words: Why would anybody (or more importantly, many people) care? Hopefully, it's not another rendition of the ice cream glove.

"Real" is often a measurement around market size; how many customers are out there, and how much are they dying to pay you?

6. "I don't believe you're right to lead this business."

Now that you've convinced your VC that this is a market going after, make it undeniable that you're the dream team to go after it. Explain why you have the perfect blend of skills, knowhow, network, and passion that no one else can flaunt. If your investor had to make only one bet on your market (as investors frequently do), why should it be on you?

7. "I'm not sure if I can afford this."

VCs allocate their funds towards new investments and follow-on rounds. Your terms must make sense in regards to their financing ability and equity interests. "Affordability" also refers to time; investors may simply pass because they're stretched thin with their existing portfolio companies.

Do your homework. Potentially save yourself some time by looking into the VC's investment stage, investment size, and board commitments.

8. "It doesn't feel right."

You may very well be something like a 90% Match, 10% Friend, 0% Enemy for your VC. You've checked every box, made them laugh on numerous occasions, and shown them a good time or two. But sometimes, the chemistry falls short of science. Don't sweat it and move on. There are many opportunities out there.

Perspective

From a WSJ article about Sycamore Networks:

Sycamore went public in 1999. Its shares more than quadrupled on their first trading day, valuing the company at $14 billion. At the time, it had booked a total of $11 million in revenue and no profits.

Last week, shareholders voted to dissolve Sycamore at a market value of $66M. One of our Fund V companes has booked over $11M in revenue without a profit. Imagine if we could take it public at $14B. We own 17% of the company - that's about $2.5B at a $14B valuation, or 11x our entire fund.

If you were a VC or an entrepreneur 1998-2000, you could get this way by doing deals like Sycamore, where a very modest degree of success led to astonishing wealth and returns. In a fund like ours the GP's would have shared about $500M in a deal like that, even though (at the time) the company had very little to show.

While it is our job to return on our funds, creating lasting, sustainable value is an implicit directive for all VCs - at least, for the ones that are truly passionate about technology. Those heady years serve as a warning for us to always take pause and think carefully in an industry that is by definition fast, competitive, and highly volatile.

Cord cutting our way back to 1980

I had a funny conversation with our analyst Kane Hsieh last week. One of Kane’s favorite games, popularized since he arrived at RRE last fall, is called “Make People Feel Old” (Kane graduated from college in 2012). As part of a wide-ranging conversation about first audio and then video content consumption, Kane dropped on me that he had never actually owned a player of physical media.

Which, after I did the Cheetohs Cheetah face-shake, kind of makes sense – if you graduated college in 2012, you were probably born in … 1990? Entered high school in 2004, well into the iPod era (no need to buy red book audio CD’s, which arrived about ten years before you were born). Never owned a DVD player even …? “Well, my parents have one”.

But it led to an interesting discussion – namely if, even in 2013, you don’t have a Blu-Ray or DVD player, how do you watch movies? “Netflix”. Right – but only the streaming side of Netflix, because … no discs for you. “Right, I use Netflix streaming”.

We talk a lot, particularly in tech, about the phenomenon of cord-cutting, of (mostly) Kane’s generation choosing not to pay the money for cable and existing on a media diet served solely by so-called “over the top” services like iTunes, Hulu and Netflix streaming. Opting out of physical media entirely is, I think, another panel in this same comic strip. The internet will provide.

This entire line of reasoning strikes me as odd. Maybe because my own media habits, built in the 80s and 90s for music when the quality and ubiquity of CD felt revelatory, making mix tapes and trading them around, and in the 90s/2000s building up a DVD collection that would always give me something good to watch and be relatively easy to store. Because I saw the Netflix DVD service as a powerful, personally fulfilling way to escape from the nearly universally dissatisfying experience of “what’s on TV right now” by allowing me to, in advance, prioritize all the movies I ever wanted to see and then arrange for them to be delivered to me with a cadence that mapped to my viewing habits. I probably watched one movie a week in those years, so having a 2 or 3 disc rotation was perfect. But maybe also odd because I intuitively assume that true “Internet natives” like Kane are more demanding of the experiences that are delivered to them, not less. And yet what Kane described – “I watch what’s on Netflix streaming” almost felt like a marginally superior version of my parents’ pre-VHS playing 13-channel television in 1979. You kind of just "flip around" until you realize - "Yeah, I never did see Empire Records ... maybe we'll watch that?"

I am still a subscriber to Netlflix and consume the streaming product from time to time via any number of my consumer electronics where Netflix has deployed their service, typically to watch back seasons of TV shows I later decided I liked or to watch documentaries. And so I’m fairly well aware that the streaming catalog … doesn’t really have very much good stuff in it outside of a few categories. The experience of browsing around on the streaming interface feels painfully like browsing the 800-channel “guide” of your local cable operator. Which is to say – it totally sucks. And you inevitably find “something to watch” rather than “something you want to watch”. The difference is pretty stark.

All of which is to say – for now I’m still happy holding onto my “legacy” mix of physical and streaming media. The majority of the movies I actually want to watch are on Netflix DVD well before they’re available on streaming (and it’s not like they are on other services either). The quality is still considerably better. I expect both of these to change over time but it was interesting and revealing to note that the generation who are allowing their needs to be met solely by the Internet are, like most generations of settlers before them, enduring a few hardships along the way.

Is it tacky to say Publishing 2.0?

About a month ago I finished an awesome science-fiction novel called WOOL. Not necessarily newsworthy (although if you enjoy sci-fi, particularly of the post-apocalyptic flavor, I strongly encourage you to read it), except WOOL was an example of a rapidly growing genre: self-published fiction.

The notion of democratized production of content isn’t even remotely new. In fact it’s so old that even the trend's moniker, “Web 2.0,” is completely passé. And yet as much as content and its production have expanded to allow ordinary people to join the conversation, the production of fiction and the novel form factor have largely been left out. Blogs have certainly created a massive firmament of non-fiction writing that has completely changed both producer and consumer’s relationships with self-expression. The rise of digital photography and platforms to both print, distribute and deploy photo assets into a variety of products have made everyone a photographer (in 2012 approximately 11% of all photos ever taken were, um, taken). GarageBand, Bandcamp and a variety of audio tools have begun (yes, just begun) to take the power of distribution out of the hands of the labels while platforms like SoundCloud provide the peer to peer platform for audio content.

WOOL is about #200 in the Kindle Store; #2 in Science Fiction, and it has no publisher. Ridley Scott is making a major Hollywood movie out of WOOL. And it’s not even the biggest self-publishing headline. Fifty Shades of Grey, while certainly not my thing (really) was responsible for one out of every twenty purchases of any book last year.

There's something even more astonishing about The Runner, by WJ Davies. The Runner is essentially fanfiction – a piece of writing that exists inside the universe created by Hugh Howey when he wrote WOOL. Fanfiction has largely been the stuff of poor jokes – assumed to be badly written stories by fanboys and fangirls who want to read about characters they like sleeping with each other so badly that they write it themselves. And yet The Runner is not only quite well written – it’s endorsed by the creator of the universe in which it takes place and is being sold in the Kindle Store - that's right, people are paying for this fanfiction.

All of which tells me that the basic structural constraints around how stories are being told, which is ultimately the core unit of fiction writing to begin with, are breaking down and very quickly. The enabling elements are all present: the rise (finally) of digital books, the creation of platforms like the Kindle Store and iBooks that collapse all the intermediate layers between author and reader, the availability of immediate, one-touch check out and delivery to our devices, the rise of subscription billing and commerce… all of these add up to a total rethinking of who gets to write fiction that we will read, and perhaps equally important – what structure that writing will take. The WOOL Omnibus reads like a standard length novel, but it’s actually 5 short novels that were published in quick succession. Because in addition to all of these enablers acting on any would-be author’s ability to reach directly into a readership, they also break down the requirements that “books” be written in a tightly defined number of pages/words in order to fit the needs of physical printing, bookstore merchandising and shipping and logistics. All of those barriers are gone. If an author wants to, she can write a story that gets published like the old serials – a new chapter every week or two. Personally if some of my favorite authors wanted to publish that way (I’m looking at you, George R. R. Martin), I’d be happy to pay $2 per month for a consistent but shorter fix (I know, I know, you could never deliver a great story that way, George – but a guy can dream).

As an investor, we’ve been very interested in the broad phenomenon of harnessing the creativity of individuals rather than a small slice of dedicated professionals. Whether it’s Quirky enabling inventors all over the world to get their ideas made into products or Makerbot giving everybody the ability to physically produce things or even the way WisdomTree gets ideas for its products from students as part of its new fund ideation process – the notion of unlocking the cognitive and creative abilities of the broader population is an enormously powerful (and still largely untapped) wave that can benefit everyone.

I’ve yet to ascertain whether or not this trend toward self publishing and the transformation we’re starting to see in the written word delivers value primarily to large platforms like Amazon and Apple or whether there is a disruptive startup approach to enabling this wave. Very interested to see what happens next.

The Flash and the Furious

If the recent exit of our portfolio company Nexsan is any indication, more and more companies are starting to take notice of low-level server technologies previously left to sys admins and IT wonks.

In 2012, the internet created more than 1,200 exabytes of new data. That’s 1,200,000,000,000 gigabytes, or 150,000,000,000 blu ray discs, which would be a stack that reaches halfway to the moon. The advent of ubiquitous sensing and monitoring and cloud computing has necessitated a lot of clever hardware and software advancements to cope with the firehose of cat pictures and stupid comments flowing through the internet.

The ability to sift through this data and find meaningful content quickly can make or break a company. Some more than others: high frequency traders hire physics Ph.Ds to optimize chips in order to squeeze every microsecond of performance out of their trading systems. That’s one extreme. For a company like Facebook, speed is the difference between unsynced social updates (a bug that existed even two years ago), or a seamless user experience. Twitter has had to add servers specifically for Justin Bieber. And what New Yorker working in tech hasn't stared blankly at a Tumblr systems maintence page?

So how do you build a fast server? We consider a very simple model of how data moves through a server:

• A query comes from the internet or a piece of software and hits the processor (CPU)

• CPU processes the query and retrieves relevant data

• CPU processes the relevant data

• CPU pushes data back to the requestor

Pretty straightforward model. However, there is a lot of nuance in the second point. How does a CPU get the data, and how does it do it quickly? To understand this, we consider the four places where data can live, in order of decreasing speed:

• Registers

• Static Random Access Memory (SRAM) <- “caches”

• Dynamic Random Access Memory (DRAM) <- colloquilally “RAM” or “Memory”

• Disk storage

Just how much faster is a register from a disk? In terms of orders of magnitude, if you were a CPU, and you need a piece of information, register data would be on the screen in front of you. Data in SRAM would be a short walk away. Data in DRAM would require you to get up and take a cab for 15 minutes to retrieve. And if you wanted disk data you would have to fly to Hong Kong and back.

Registers are incredibly fast, tiny pieces of memory on the CPU die (colloquially "the chip") that hold small pieces of data the CPU is immediately working on. This is the domain of chipmakers (Intel, Qualcomm, etc) and essentially a black box to programmers. SRAM is a “cache” – slower than registers, but faster than DRAM, it allows the processor put temporarily store important data. SRAM caches are also on the CPU die, but might also be on a motherboard.

The CPU, it’s registers and caches are connected via a “north bridge” to DRAM (“RAM” or “Main Memory” from now on) and through a “south bridge” to disk storage. Memory and storage is where storage companies come into play.

Memory sits on motherboards and the hardware form factor is standardized, so companies focusing on main memory solutions tend to be software based. Memcached is an example of a product that does databasing within main memory, and MemSQL is another. The reason there’s value in software at the memory level is because caches and memory are both relatively small in terms of data capacity; if the data you want is NOT in a cache or memory, you get what’s known as a “thrash”, and your CPU has to go into storage to retrieve it. This might only take milliseconds, but for a processor, that can be millions of wasted computations. Clever software makes sure that the data you'll most likely need will be in main memory when a CPU needs it. But it's not cost effective to store all data in memory, so we need to cheaper, slower disk storage.

For a long time, disk storage has been spinning magnetic hard disks. While incredibly cheap relative to memory, they were much slower – that means expensive servers would be twiddling their thumbs (and burning through power) waiting for data to come from storage. This meant that historically, those that have needed absolutely bleeding edge performance spent a lot of money on main memory.

However, the recent decline in the prices of flash storage (similar to the technology in thumb drives), also known as SSD ("Solid State Disk"), has brought the speed of disk data retrieval a few orders of magnitudes closer to that of main memory data retrieval. SSD is a bit of a misnomer - there is no "disk," in the traditional sense, in an SSD - just chunks of flash storage.

You can’t just drop in flash storage and call it a day though – with exponentially larger data sets, the time it takes to find data within a database (even on flash) can be a bottleneck. That’s why we see software plays in storage, such as 10gen and Aerospike; while these are agnostic to the storage medium (flash versus spinning disk), they work best with SSDs since SSDs are strictly faster than spinning disks - and therefore software and hardware compliment each other at the storage level.

The long and short of it all is that performance is a delicate dance of hardware and software. More efficient performance allowers servers to be run cheaper, and faster performance often correlates directly to higher revenues for companies. Understanding where bottlenecks are in datacenters - and the various hardware and software solutions that can fix them - are valuable to any modern company.

Some of the above examples are based on the excellent course notes of Prof. Stephen Chong, for those of you want a more technical reference. [source]

Eugenia Koo

With the start of the new year we are happy to announce a new addition to our team. Eugenia Koo has joined RRE as an Analyst focused on identifying new investment opportunities and increasing our involvement with the community of innovators in New York.

Eugenia is already a leader within New York City's entrepreneurial community, having been an East Coast contributor for The Next Web and co-founder of Hack'n Jill.

As her background suggests, Eugenia is analytical, diligent, and perceptive. She's also very personable. You can introduce yourself to her at @itwentviral or at eugenia@rre.com.

The Holy Grail of Cloud

A difficult part of being a VC is evalutating a company at all levels, from engineering feasbility to business viability. Ove the coming weeks I will try to explain some complex engineering concepts in plain English.

A term that is being tossed around more and more these days is homomorphic encryption, and it’s important to understand what it is when analyzing the value of cloud services targeted towards large institutions that have lots of sensitive data. (If you are mathematically inclined, the Wiki dives a lot deeper).

Right now, many companies hesitate to move to fully hosted data solutions because they don’t want to put sensitive data on servers they don’t control (ie the cloud). For instance, if Acme. Co has all sensitive data hosted on Microsoft Azure, and the DOJ subpoenas Microsoft for Acme’s data, they get all that data from Microsoft. Or a rogue employmee might swipe the disks (unlikely, but paranoia is a strong deterrent).

“Why not encrypt it?” you might ask. The problem with cloud now is that if I want to do computation on data I have in the cloud, it has to be unencrypted. Why? Consider the statement “4 + 3 = 7.” Let 4 and 3 represent some really confidential financial data, and 7 is a confidential result of some function, in this case addition. If I want to store 4 and 3 in the cloud, I encrypt them. Pretend our protocol I’m using encrypts 4 to AB and 3 to EF, and 7 to WX. I can now safely store AB and EF in the cloud. But I need to find out with the confidential result of 4+3 is. In the cloud, I would have to do AB + EF, since my data is encrypted. But that’s a meaningless statement. AB + EF doesn’t result in anything. Therefore, to do any computation in the cloud, unencrypted data has to exist for some period of time in the cloud. And that’s a dealbreaker for many companies.

Homomorphic encryption is an extraordinarily clever crypto system such that AB + EF = WX. Thta is, addition on two pieces of encrypted data results in the encrypted version of the unencrypted result of addition on the unencrypted versions of the two pieces of original data. A system is fully homomorphic if addition and multiplication can both be computed on encrypted data.

To make that rigorous:

• Let the encryption function be P()
• Let a, b, c, and d be data

A homomorphic encryption is one such that P(a) + P(b) = P(c) and P(a) * P(b) = P(d) if and only if (a + b = c) and (a * b = d). Homomorphic encryption is sort of a holy grail of enterprise cloud, because it means no unencrypted data will ever touch a cloud server.

Unfortunately, homomorphic encryption does not exist. At least, not in a usable way. However, there are companies that provide what I call “practically homomorphic” encryption. That is, software that isn't actually homomorphic but behaves like it is. This is usually accomplished via a referential set of proprietary metadata that is attached to the encrypted data. The software's algorithims then use the metadata to approximate functions on the original data.

For parsing certain data, such as searching email, I don’t need rigorous homomorphic encryption; unlike acounting, which has to give exact, deterministic results, email search results that are close enough (eg. only fails when searching a certain Greek symbol) represent a value added if it allows a company to use a cloud hosted email server (Office 365, Gmail) without worrying about sensitive data existing on the hosting server.

What does this all mean? Many remain bearish on the value of hosted storage to companies with a lot of sensitive information. True homomorphism, while still the domain of academic researchers, could potentially change all that; until then, companies like CipherCloud, which just raised $30M, will make practically homomorphic products for certain sets of data, and companies will timidly build out hybrid clouds.